Using In-Memory Databases in Data Science

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • Redis

    Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.

    Redis is an in-memory database and an open-source streaming engine with an IMDB data structure server that supports multiple data sets and data streams. This open-source platform has high throughputs and lower bandwidth due to its in-memory features that lead to faster processing of big data in data science applications.

  • Aerospike

    Aerospike Database Server – flash-optimized, in-memory, nosql database

    Aerospike is a real-time cloud structured platform with good performance capabilities. This IMDB platform allows enterprises to perform their operations in real time through the hybrid memory and parallelism model.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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